A POD-NN surrogate trained on FEM solutions of steady-state diffusion-reaction equations delivers 956x speedup with 15% mean relative L2 error for nutrient transport and salinity predictions.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.NA 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Data-Driven Surrogate Models for Agromaritime Applications: Finite Element-Neural Network Integration
A POD-NN surrogate trained on FEM solutions of steady-state diffusion-reaction equations delivers 956x speedup with 15% mean relative L2 error for nutrient transport and salinity predictions.